2023-10-06 07:50:16 +00:00
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from __future__ import annotations
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2023-10-07 07:02:48 +00:00
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from aiohttp import ClientSession
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2023-10-09 08:22:17 +00:00
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from ..typing import AsyncResult, Messages
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2023-10-05 03:13:37 +00:00
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from .base_provider import AsyncGeneratorProvider
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class AiAsk(AsyncGeneratorProvider):
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url = "https://e.aiask.me"
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2023-10-27 20:59:14 +00:00
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supports_message_history = True
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2023-10-05 03:13:37 +00:00
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supports_gpt_35_turbo = True
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2023-11-13 17:58:52 +00:00
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working = False
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2023-10-05 03:13:37 +00:00
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@classmethod
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async def create_async_generator(
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cls,
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model: str,
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messages: Messages,
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proxy: str = None,
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2023-10-05 03:13:37 +00:00
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**kwargs
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2023-10-09 08:22:17 +00:00
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) -> AsyncResult:
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2023-10-05 03:13:37 +00:00
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headers = {
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"accept": "application/json, text/plain, */*",
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"origin": cls.url,
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"referer": f"{cls.url}/chat",
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}
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2023-10-07 07:02:48 +00:00
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async with ClientSession(headers=headers) as session:
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2023-10-05 03:13:37 +00:00
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data = {
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"continuous": True,
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"id": "fRMSQtuHl91A4De9cCvKD",
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"list": messages,
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"models": "0",
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"prompt": "",
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"temperature": kwargs.get("temperature", 0.5),
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"title": "",
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}
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buffer = ""
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rate_limit = "您的免费额度不够使用这个模型啦,请点击右上角登录继续使用!"
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2023-10-09 08:22:17 +00:00
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async with session.post(f"{cls.url}/v1/chat/gpt/", json=data, proxy=proxy) as response:
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2023-10-05 03:13:37 +00:00
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response.raise_for_status()
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async for chunk in response.content.iter_any():
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buffer += chunk.decode()
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if not rate_limit.startswith(buffer):
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yield buffer
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buffer = ""
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elif buffer == rate_limit:
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raise RuntimeError("Rate limit reached")
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